Between the dawn of civilisation and 2003, five exabytes of data was created; now that amount is generated every two days, according to Hal Varian, Chief Economist at Google.
An exabyte is a large unit of computer data storage, comprising a billion gigabytes; one gigabyte is one billion bytes. An exabyte of storage could contain 50 000 years' worth of DVD-quality video, says Richard Topham, director of product and propositions in Experian's EMEA Decision Analytic division.
I draw attention to these statistics to demonstrate the explosion of data in our midst. And if you regard these numbers as vast, consider that IDC estimates that by 2020, we will witness a 44-times increase in data, 80% of which will be unstructured data accessed through one trillion connected devices.
According to Gartner, by 2015, tablet unit sales will be 326 million and smartphone unit sales one billion. Gartner also suggests that last year more than 140 million people worldwide used their mobile phones to process $85 billion in total payment volume - 38% more than on 2010.
Of particular and profound relevance is that data is becoming the new raw material of business - an economic input almost on a par with capital and labour.
Indeed, never before has there been an opportunity to have such deep access to user behavioural and demographic data to create actionable insight. A corollary observation is that customers who use social networking to interact with an organisation are more profitable and loyal than those who do not.
The critical driver in optimising the mountain of data is an awareness of how vital it is to put the customer first while balancing regulation with innovation.
In its quest to strike that balance, management needs to weigh up numerous (often contrasting) criteria. It must:
* Equate growth and expansion with the simultaneous need for a tight, conservative approach to risk;
* Innovate and test ideas against a background of constantly rising customer expectations;
* Satisfy customers' ever-widening demand for new technology while overcoming the difficulties posed by outdated systems; and
* Appreciate just how crucial is speed and accuracy of decisions.
A continual focus on innovation and improvement will create value through empowering management to make informed decisions, utilising and optimising both internal and external data assets, and using technology that enables, rather than constrains, the business.
Management should be aware of each and every management tool able to enhance performance. A prime example is the use of a sophisticated decision engine to enable organisations to use their internal and external data in all customer interactions.
Other steps designed to ensure that the right decisions are made include:
* Using off-the-shelf-decisioning solutions which have been built by experts and already embed best practice;
* Embedding marketing and economic data into risk scorecards to provide a more broad view of the customer;
* Addressing application fraud with a national fraud prevention service which shares data across the industry and tackles fraud through co-operation between lenders; and
* Giving the business users the tools to be agile, innovative and customer-focused to enable the organisation to react to market changes, test new strategies and use any new data sources that improve insight about customer behaviour.
Experian Decision Analytics software solutions are being increasingly recognised as an invaluable aid to managing customer decisions across the full customer life cycle, today and into the future. That's because today's decision management software is created with the business user and complex data in mind, making it easier to use and quicker to implement, and so achieving a faster return on investment. The Experian Decision Analytics software platform, PowerCurve, is therefore ideally suited for clients' current and future needs.
The approach is typified by a flexible, intuitive graphical user environment for the creation and administration of value-adding risk management strategies. It uniquely combines predictive analytics, business rules processing, and strategy reporting capabilities in a single, integrated environment.
As a single centralised automated decisioning platform, PowerCurve combines data to find the right customers by implementing strategies at every customer interaction point. Indeed, it ensures the company only acquires the right customers; that it takes on those with a risk profile that matches the company's strategy.
It almost goes without saying that management should understand and prioritise the organisation's most profitable customers. Centralised automated decisioning actively targets and acquires them before the competition through the intelligent use of marketing and customer data sources.
This competitive advantage can be achieved, for example, through the use of all data available to set competitive and appropriate terms at the point of acquisition to improve take-up rates, minimise bad debt, optimise capital adequacy and ultimately maximise profitability.
The value of knowing all there is to know about existing and potential customers cannot be exaggerated. Organisations must adopt new data sources to build the rich history of a customer more deeply to understand customer relationships, changes in behaviour and risk exposure, by gaining a holistic customer level view.
From that platform, the organisation is able to build, nurture and maximise lasting, profitable customer relationships while fully leveraging all available data assets to understand telltale behaviour patterns, bearing in mind that people's profiles change over time.
With a view to generating revenue growth while keeping costs and losses at a minimum, attention should focus on maximising the value of every interaction, whether that is in the customer prospecting, on-boarding, account and customer management stage.
In all their interaction with their financial organisations, customers expect great service and quick responses. But if that is all the organisation provides, it is missing out on a whole gamut of opportunities - like cross-selling, retention activity, pre-emptive strategies and product promotion, strategies that their competitors might well be employing in these times where customer expectations are rising, response times need to fall and the need to understand and manage customer profitability is at an all-time high.
Ultimately, to facilitate the creation of specific decisioning models, flexibility is vital; flexibility to implement more granular segments to make offers that exactly match the customers' needs and data is the medium through which that flexibility is attained. Without automated decisioning solutions, these new sources of data become overwhelming and the result is that an organisation misses out on an opportunity to drive its profitability while increasing customer satisfaction and behavioural insight.
Share